keras-yolo3
Deep-SORT-YOLOv4
| keras-yolo3 | Deep-SORT-YOLOv4 | |
|---|---|---|
| 1 | 1 | |
| 1,606 | 492 | |
| - | - | |
| 0.0 | 0.0 | |
| 8 months ago | about 3 years ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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keras-yolo3
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What’s Destroying My Yard? Pest Detection with Raspberry Pi
I've always been facinated by the usage of the Pi. I think of the methods used when you have a pi, versus not having one. It looks like a fun project if you have all the parts, but I don't so I thought of this alternative!
A method I thought of was just a camera that will utilize yolo3 https://github.com/experiencor/keras-yolo3 or just an always on security camera that you can just skip through the video to see all the activity with less setup, and seeing what animals cause issues. The jetson for faster 'edgey' visual ML models might be an option for those who want a stronger NPU, but using online GPU/NPU tokens and GPUs on computers if you don't need live feedback is very effective.
Deep-SORT-YOLOv4
What are some alternatives?
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
ultralytics - NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
YOLO-Coco-Dataset-Custom-Classes-Extractor - Get specific classes from the Coco Dataset with annotations for the Yolo Object Detection model for building custom object detection models.